Langfuse vs LangWatch

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan: Both have one
Public API: Both have one
Best fit: Langfuse: Engineering teams running LLM apps or agents in production who need traces and cost tracking · LangWatch: Teams shipping conversational agents that need pre-release regression testing
Trust score: About even — Langfuse 80, LangWatch 82
Status: Both up at our last check — Langfuse Oct 29, 2026, LangWatch Oct 16, 2026

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

LangfuseOpen-source LLM engineering platform for tracing agents, versioning prompts, running evals and tracking cost, hosted or self-hosted.

LangWatchSimulates user scenarios against LLM agents, scores the answers and traces every step in production

Side by side

Fact	Langfuse	LangWatch
Category	LLM Observability & Evaluation	LLM Observability & Evaluation
Pricing model	Freemium	Freemium
Starts at	$29/mo	—
Public API	Yes	Yes
Trust score	80 / 100	82 / 100
Platforms	Web, API	Web, API
Company	Langfuse GmbH	LangWatch B.V.
Launched	2023	—
Last verified	Oct 29, 2026	Oct 16, 2026

What our research says

Langfuse

Langfuse is a strong default for teams that want tracing, prompt versioning and evaluations in one open-source tool, with the option to keep data on their own infrastructure. Teams that only want a hosted logging proxy with no SDK work, or that need guaranteed enterprise SSO without paying for add-ons, may find simpler or more bundled options.

Pros

MIT-licensed core that can be self-hosted without usage limits
Covers tracing, prompt management, evaluation and dashboards in one product
Generous free cloud tier and unlimited users from the $29 Core plan
OpenTelemetry support and SDKs for Python and JavaScript

Cons

Usage above the included 100k units is billed extra, so busy apps pay more than the headline price
Free tier keeps only 30 days of data and two users
Enterprise SSO and RBAC require the $300 Teams add-on on Pro or the Enterprise plan

LangWatch

The scenario simulation is what sets it apart: instead of only watching production traces, it drives synthetic users at your agent so failures show up before release. Apache 2.0 licensing means you can self-host if the euro seat pricing or data residency bothers you.

Pros

Agent simulation drives realistic scenarios rather than only recording production
Evaluators, traces and prompt versioning live in the same product
Core is open source under Apache 2.0, so self-hosting avoids seat pricing
Free Developer tier includes 50k events a month rather than a time-limited trial

Cons

Growth is billed per core seat, so cost scales with team size as well as volume
Free tier keeps data only 14 days and caps you at 2 users
Pricing is euro-denominated with no USD equivalent published
Event overage at EUR 5 per 100k is easy to overlook when agents get chatty

Which one fits

Choose Langfuse if you need

Engineering teams running LLM apps or agents in production who need traces and cost tracking
Organisations that must self-host observability data for compliance
Teams that want prompts, datasets and evals tied to the same traces

Choose LangWatch if you need

Teams shipping conversational agents that need pre-release regression testing
Engineers who want traces, evals and prompt versions in one tool
European teams needing EU-hosted or self-hosted LLM observability